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Machine Learning Performance Engineer- World-Leading Prop Trading Fund | London, UK

Oxford Knight
London
4 months ago
Applications closed

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Machine Learning Performance Engineer - World-Leading Prop Trading Fund

Summary:
An exciting opportunity to work at a tech-centric proprietary trading fund that trades a wide range of financial products, with offices across the globe. We are seeking an experienced engineer with expertise in low-level systems programming and optimization to join our growing ML team.

Machine learning is central to our operations. Your focus will be to optimize the performance of our models, including training and inference. This involves efficient large-scale training, low-latency real-time inference, and high-throughput research inference. The role requires a holistic approach, including improvements in CUDA, storage systems, networking, and host- and GPU-level considerations.

The ideal candidate is a smart, curious software engineer who enjoys solving complex problems and has a strong desire to learn new skills.

Requirements:

  1. Understanding of modern ML techniques and tools, with a focus on performance.
  2. Systems knowledge and experience to debug end-to-end training performance issues.
  3. Low-level GPU knowledge, including CUDA or similar GPU programming (PTX, SASS, warps, cooperative groups, Tensor Cores, memory hierarchy).
  4. Experience with debugging and optimization tools such as CUDA GDB, NSight Systems, NSight Compute.
  5. Familiarity with libraries like Triton, CUTLASS, CUB, Thrust, cuDNN, and cuBLAS.

Benefits:

  • Market-leading salaries
  • Generous benefits including health, mental health, holiday entitlement, parental leave, retirement plans, private gym
  • Focus on learning and development, including tuition reimbursement
  • Recreation spaces with meals and snacks

We review all applications carefully. Due to high volume, we may not be able to respond to unsuccessful applicants.

Contact:

If you are a good fit, please reach out:

Dan Hampton

Email:

Phone:

LinkedIn: linkedin.com/in/dan-hampton-ab029392


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